In this paper, new digital predistortion (DPD) solutions for power amplifier (PA) linearization are proposed, with particular emphasis on reduced processing complexity in future 5G and beyond wideband radio systems. The first proposed method, referred to as the spline-based Hammerstein (SPH) approach, builds on complex spline-interpolated lookup table (LUT) followed by a linear finite impulse response (FIR) filter. The second proposed method, the spline-based memory polynomial (SMP) approach, contains multiple parallel complex spline-interpolated LUTs together with an input delay line such that more versatile memory modeling can be achieved. For both structures, gradient-based learning algorithms are derived to efficiently estimate the LUT control points and other related DPD parameters. Large set of experimental results are provided, with specific focus on 5G New Radio (NR) systems, showing successful linearization of multiple PA samples as well as a 28 GHz active antenna array, incorporating channel bandwidths up to 200 MHz. Explicit performance-complexity comparisons are also reported between the SPH and SMP DPD systems and the widely-applied ordinary memory-polynomial (MP) DPD solution. The results show that the linearization capabilities of the proposed methods are very close to that of the ordinary MP DPD, particularly with the proposed SMP approach, while having substantially lower processing complexity.

Gradient-Adaptive Spline-Interpolated LUT Methods for Low-Complexity Digital Predistortion

In modern communication systems advanced techniques such as digital predistortion (DPD) are required to satisfy stringent demands on transmitter linearity and efficiency. DPD, however, increases the hardware and computational complexity of transmitters. In this article we show that the computational complexity of DPD adaptation can be drastically reduced if a low number of samples is properly selected for DPD adaptation. For this purpose we propose methods of sample selection for DPD adaptation. Among the proposed methods, the highest computational complexity reduction is achieved by a method based on the histogram of signal magnitudes, optimised with respect to characteristics of the radio frequency power amplifier and of the transmitted signal. Simulations indicate that this proposed method can reduce the computational complexity of DPD adaptation by a factor of up to 400 while the linearisation performance of conventional methods is preserved. Besides simulations for three models of distinct power amplifiers, measurements on a real power amplifier further verify the linearisation capabilities of the proposed methods.

On Feedback Sample Selection Methods Allowing Lightweight Digital Predistorter Adaptation

Orthogonal Time Frequency Space (OTFS) modulation has recently been proposed for communication in doubly selective channels. Together with millimeter waves, OTFS seems to be one of the promising candidates for beyond-5G communication systems. In this paper we present the performance of an OTFS system with an Linear Minimum Mean Square Error (LMMSE) equalizer in the presence of main hardware impairments extracted from our millimeter-wave setup in the 60 GHz band.

OTFS Modulation and Influence of Wideband RF Impairments Measured on a 60 GHz Testbed

This letter proposes a mesh-selecting (MeS) method for complex-valued signals oriented at significantly reducing the training data required to extract the parameters of mathematical models for characterizing the nonlinear behavior of power amplifiers or digital predistortion linearizers. Experimental results will show the advantages of the proposed MeS method when properly combined with dimensionality reduction techniques. A reduction of the parameters’ identification computational complexity by a factor of 65 can be achieved with respect to training with consecutive samples and employing the commonly used QR least-squares solution.

Mesh-Selecting for Computational Efficient PA Behavioral Modeling and DPD Linearization

Abstract The evolution of the fifth-generation (5G) new radio (NR) has progressed swiftly since the third generation partnership project (3GPP) standardized the first NR version (Release 15) in mid-2018. Nowadays, the world’s leading carriers are competing to provide various commercial services over 5G networks. Looking ahead to 2025 and beyond, it is expected that over 6.5 million 5G base stations will be installed to offer services to over 58% of the world’s population via over 100 billion 5G connections. Following the rapid development of 5G, an increasing number of commercialization use cases will drive the 5G network to continuously improve performance and expand capabilities. Hence, it is the right time to consider a well-defined framework and standardization for 5G NR evolution (5G-Advanced) to support commercialization between 2025 and 2030. First, this study addresses the key driving forces, requirements, usage scenarios, and capabilities of 5G-Advanced; then, it highlights the main technological challenges and introduces the top 10 promising technological directions in detail. Finally, other fascinating technological directions in 5G-Advanced are shortly mentioned. 

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A new 5G radio evolution towards 5G-Advanced

As the data throughput is still increased in the wireless communication systems, it is required to efficiently utilise the radio frequency spectrum which usually requires linear transmitters Consequently methods as a digital predistortion (DPD) are developed to linearise nonlinear power amplifiers To extract precise parameters for the DPD it is essential to finely synchronise measured feedback signal with the known transmitted signal In this paper we propose an analytical method for the fractional sample period time synchronisation suitable for DPD signals Finally benefits of the proposed method are presented on results of its usage for the DPD linearisation using a measurement test-bed

Analytical method of fractional sample period synchronisation for digital predistortion systems

Interference between users in adjacent channels negatively affects throughput of mobile networks. In this paper we aim at cancellation of interference caused by a nonlinear power amplifier in a generalized orthogonal frequency division system. We propose an interference cancellation method to subtract these out-of-band emissions from the received signal. In contrast to state-of-the-art methods, our proposed method employs over-the-air estimation of power amplifier model parameters together with a particular frequency domain filtering method that allows to generate the required training data. The proposed interference cancellation method is also verified by an experiment on a software defined radio test bench.

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Adjacent Channel Interference Cancellation in FDM Transmissions

Digital predistorters (DPD) are used in modern communication systems to linearise nonlinear power amplifiers (PA) and maximise power efficiency For their function, a feedback signal from the PA output is required A conventional DPD uses a quadrature mixer and two analogue-to-digital converters (ADC) which consume additional power and increase system complexity In this paper we have proposed an innovative technique which allows to use a nonquadrature RF mixer with one ADC in the feedback path The DPD adaptation is noniterative and based on favoured indirect learning architecture Firstly, the forward PA model is estimated and subsequently it is used to train DPD coefficients We have verified and compared the proposed method with other DPD architectures in simulations The results show that the proposed architecture can achieve the same results as a DPD with complex feedback samples and the other real-valued feedback architectures

Digital Predistorter with Real-Valued Feedback Employing Forward Model Estimation

In this paper, we present the quantitative study of the effects of the selected most important transceiver imperfections on the performance of digital baseband pre-distortion linearizers. Starting from the power amplifier model identification based on the measured data captured using the low-cost software defined radio platform (USRP), we evaluate the performance in term of out-of-band signal emissions at the power amplifier output for the case of typical representative of signals envisaged for fifth generation (5G) of mobile communication systems — filtered OFDM. The results are presented for the values of imperfections (IQ imbalances, DC offset) swept within the range of values corresponding to simple, commercially available wireless front-ends. We highlight the fact that the front-end imperfections can significantly affect the influence of pre-distorters.

Michal Harvanek

Papers

On Feedback Sample Selection Methods Allowing Lightweight Digital Predistorter Adaptation

Analytical method of fractional sample period synchronisation for digital predistortion systems

Adjacent Channel Interference Cancellation in FDM Transmissions

Digital Predistorter with Real-Valued Feedback Employing Forward Model Estimation

Influence of transceiver imperfections to digital pre-distortion linearization — Application to 5G waveforms